Motion in tissues has always been problematic for in vivo imaging in high-resolution optical systems. The difficulties imposed by involuntary retinal and cardiac movements with respect to acquisition and processing of artifact-free in vivo data are discussed, respectively, by Považay et al., “Impact of enhanced resolution, speed and penetration on three-dimensional retinal optical coherence tomography,” Opt. Exp., vol. 17, pp. 4134-50 (2009), and Ablitt et al., “Predictive cardiac motion modeling and correction with partial least-squares regression,” IEEE Trans. Med. Imaging, vol. 23, pp. 1315-24 (2004), both of which papers are incorporated herein by reference.
A number of approaches have been used both to correct, and to avoid, motion. For cardiac and respiratory imaging, synchronization with the beating heart or imaging between breaths, respectively, is common in magnetic resonance imaging and ultrasound. When motion is involuntary and random in nature, though, the only options are to scan fast enough to avoid motion, compensate for motion during imaging, or correct the motion in post-processing. In optical coherence tomography (OCT), 2-D cross sections are easily acquired without motion artifacts, but full 3-D volumes often still require some amount of motion compensation or correction—especially for in vivo retinal imaging.
For motion correction in post-processing, motion must be measured in some way. Depending on the application, the required precision of the measured motion will change. For traditional amplitude imaging, the required precision depends only on the resolution of the imaging system. Thus, for OCT, assuming features with sufficient contrast exist, separate incoherent imaging systems are often used in conjunction with the acquired data to rapidly track and correct for motion, as exemplified, for example, by Felberger et al., “Adaptive Optics SLO/OCT for 3D imaging of human photoreceptors in vivo,” Biomed. Opt. Exp., vol. 5, pp. 439-56 (2014), incorporated herein by reference. For imaging modalities such as Doppler OCT, the required precision of axial motion tracking is well below the resolution of the system as these modalities rely on the phase of backscattered light. It is possible, though, to utilize spatial oversampling and the measured phase in depth to correct this motion, as taught by White et al., “In vivo dynamic human retinal blood flow imaging using high-speed spectral domain optical coherence tomography,” Opt. Exp., vol. 11, pp. 3490-97 (2003), incorporated herein by reference. Transverse motion correction in Doppler OCT requires the same precision as traditional OCT amplitude imaging, and thus can use similar tracking and correction techniques as other OCT imaging systems.
Interferometric Synthetic Aperture Microscopy (ISAM), Computational Adaptive Optics (CAO), Digital Adaptive Optics (DAO), and Holoscopy are all computed imaging techniques which can computationally correct defocus and optical aberrations, but are known to have especially high sensitivity to motion. This is true for even the swept-source full-field techniques (DAO and Holoscopy). Even though the transverse phase relationship is preserved for each individual wavelength of light, the full spectrum, which is required for the reconstruction, is measured over time, and is therefore susceptible to motion. In addition, these techniques may actually be more susceptible to motion due to the long interrogation length of each point in the sample.
Axially, the stability requirements of computed optical interferometric techniques in general can be the strictest, as they utilize the phase of the measured data. This means that even motion on the order of the wavelength of light can interfere with the desired reconstruction.
For the transverse dimensions, defocus and aberration correction techniques are unique in that the tolerable level of motion can be well below the resolution of the imaging system. This occurs in the presence of aberrations where, when diffraction-limited performance is not achieved at the time of imaging, the stability requirements for correcting the aberrations actually increases due to a longer interrogation length. Therefore, a separate incoherent imaging system with the same non-diffraction-limited performance cannot be used to measure motion with the required precision because of the lack of sharp high-contrast features.
Prior art methods required either stable data at the time of imaging or use of a phase reference, such as a coverslip placed on the sample or tissue, to compensate for optical path length fluctuations, as taught by Ralston et al., “Real-time interferometric synthetic aperture microscopy,” Opt. Exp., vol. 16, pp. 2555-69 (2008), which is incorporated herein by reference. Additionally, it has been shown that motion could be corrected by using only the acquired OCT data for numerical defocus correction and other phase-resolved techniques, however these techniques, described in the following references, both incorporated herein by reference, are all, necessarily, restricted to one- or two-dimensional motion correction:                Lee, et al., “Motion correction for phase-resolved dynamic optical coherence tomography imaging of rodent cerebral cortex,” Opt. Express, vol. 19, pp. 21258-70 (2011); and        Liu, et al., “Phase registration based on matching of phase distribution characteristics and its application in FDOCT,” Opt. Exp., vol. 21, pp. 13241-55 (2013).        
Phase stability assessment has also been applied in a tomographic context, by White et al., “In vivo dynamic human retinal blood flow imaging using ultra-high-speed spectral domain optical Doppler tomography,” Opt. Exp., vol. 11, pp. 3490-97 (2003), which is incorporated herein by reference. White (2003) required incidence of light onto the sample by reflection from a fixed mirror so that all phase differences could be attributed solely to movement within the sample.
For many applications, however, it is desirable that a method be provided for assessing stability using the phase while allowing for a scanned imaging configuration. This however adds the complication of assessing stability in all three dimensions, as is provided in accordance with the teachings of the present invention, as now described.